A predicted physicochemically distinct sub-proteome associated with the intracellular organelle of the anammox bacterium Kuenenia stuttgartiensis

Background: Anaerobic ammonium-oxidizing (anammox) bacteria perform a key step in global nitrogen cycling. These bacteria make use of an organelle to oxidize ammonia anaerobically to nitrogen (N2) and so contribute approximately 50% of the nitrogen in the atmosphere. It is currently unknown which proteins constitute the organellar proteome and how anammox bacteria are able to specifically target organellar and cell-envelope proteins to their correct final destinations. Experimental approaches are complicated by the absence of pure cultures and genetic accessibility. However, the genome of the anammox bacterium Candidatus "Kuenenia stuttgartiensis" has recently been sequenced. Here, we make use of these genome data to predict the organellar sub-proteome and address the molecular basis of protein sorting in anammox bacteria. Results: Two training sets representing organellar (30 proteins) and cell envelope (59 proteins) proteins were constructed based on previous experimental evidence and comparative genomics. Random forest (RF) classifiers trained on these two sets could differentiate between organellar and cell envelope proteins with ~89% accuracy using 400 features consisting of frequencies of two adjacent amino acid combinations. A physicochemically distinct organellar sub-proteome containing 562 proteins was predicted with the best RF classifier. This set included almost all catabolic and respiratory factors encoded in the genome. Apparently, the cytoplasmic membrane performs no catabolic functions. We predict that the Tat-translocation system is located exclusively in the organellar membrane, whereas the Sec-translocation system is located on both the organellar and cytoplasmic membranes. Canonical signal peptides were predicted and validated experimentally, but a specific (N- or C-terminal) signal that could be used for protein targeting to the organelle remained elusive. Conclusions: A physicochemically distinct organellar sub-proteome was predicted from the genome of the anammox bacterium K. stuttgartiensis. This result provides strong in silico support for the existing experimental evidence for the existence of an organelle in this bacterium, and is an important step forward in unravelling a geochemically relevant case of cytoplasmic differentiation in bacteria. The predicted dual location of the Sec-translocation system and the apparent absence of a specific N- or C-terminal signal in the organellar proteins suggests that additional chaperones may be necessary that act on an as-yet unknown property of the targeted proteins

MultiMetEval: comparative and multi-objective analysis of genome-scale metabolic models

Comparative metabolic modelling is emerging as a novel field, supported by the development of reliable and standardized approaches for constructing genome-scale metabolic models in high throughput. New software solutions are needed to allow efficient comparative analysis of multiple models in the context of multiple cellular objectives. Here, we present the user-friendly software framework Multi-Metabolic Evaluator (MultiMetEval), built upon SurreyFBA, which allows the user to compose collections of metabolic models that together can be subjected to flux balance analysis. Additionally, MultiMetEval implements functionalities for multi-objective analysis by calculating the Pareto front between two cellular objectives. Using a previously generated dataset of 38 actinobacterial genome-scale metabolic models, we show how these approaches can lead to exciting novel insights. Firstly, after incorporating several pathways for the biosynthesis of natural products into each of these models, comparative flux balance analysis predicted that species like Streptomyces that harbour the highest diversity of secondary metabolite biosynthetic gene clusters in their genomes do not necessarily have the metabolic network topology most suitable for compound overproduction. Secondly, multi-objective analysis of biomass production and natural product biosynthesis in these actinobacteria shows that the well-studied occurrence of discrete metabolic switches during the change of cellular objectives is inherent to their metabolic network architecture. Comparative and multi-objective modelling can lead to insights that could not be obtained by normal flux balance analyses. MultiMetEval provides a powerful platform that makes these analyses straightforward for biologists. Sources and binaries of MultiMetEval are freely available from https://github.com/PiotrZakrzewski/MetEv​al/downloads

Linking genomics and metabolomics to chart specialized metabolic diversity

Microbial and plant specialized metabolites constitute an immense chemical diversity, and play key roles in mediating ecological interactions between organisms. Also referred to as natural products, they have been widely applied in medicine, agriculture, cosmetic and food industries. Traditionally, the main discovery strategies have centered around the use of activity-guided fractionation of metabolite extracts. Increasingly, omics data is being used to complement this, as it has the potential to reduce rediscovery rates, guide experimental work towards the most promising metabolites, and identify enzymatic pathways that enable their biosynthetic production. In recent years, genomic and metabolomic analyses of specialized metabolic diversity have been scaled up to study thousands of samples simultaneously. Here, we survey data analysis technologies that facilitate the effective exploration of large genomic and metabolomic datasets, and discuss various emerging strategies to integrate these two types of omics data in order to further accelerate discovery

Doxorubicin-induced DNA Damage Causes Extensive Ubiquitination of Ribosomal Proteins Associated with a Decrease in Protein Translation

Protein posttranslational modifications (PTMs) play a central role in the DNA damage response. In particular, protein phosphorylation and ubiquitination have been shown to be essential in the signaling cascade that coordinates break repair with cell cycle progression. Here, we performed whole-cell quantitative proteomics to identify global changes in protein ubiquitination that are induced by DNA double-strand breaks. In total, we quantified more than 9,400 ubiquitin sites and found that the relative abundance of similar to 10% of these sites was altered in response to DNA double-strand breaks. Interestingly, a large proportion of ribosomal proteins, including those from the 40S as well as the 60S subunit, were ubiquitinated in response to DNA damage. In parallel, we discovered that DNA damage leads to the inhibition of ribosome function. Taken together, these data uncover the ribosome as a major target of the DNA damage response.This work is funded by a TOP-GO grant from the Netherlands Organization for Scientific Research (NWO ZonMW 912100651 to R.H.M., S.M., and V.A.H.). I.G.S. was supported with a postdoctoral fellowship from the Basque Country Government (Spain). We thank Christian Frese and Teck Yew Low for fruitful discussions. We also thank Teck Yew Low for submitting the raw files and annotated spectra to PRIDE. We thank Fabricio Loayza-Puch for his technical help with the sucrose gradients

Mutations in LRRC50 Predispose Zebrafish and Humans to Seminomas

Seminoma is a subclass of human testicular germ cell tumors (TGCT), the most frequently observed cancer in young men with a rising incidence. Here we describe the identification of a novel gene predisposing specifically to seminoma formation in a vertebrate model organism. Zebrafish carrying a heterozygous nonsense mutation in Leucine-Rich Repeat Containing protein 50 (lrrc50 also called dnaaf1), associated previously with ciliary function, are found to be highly susceptible to the formation of seminomas. Genotyping of these zebrafish tumors shows loss of heterozygosity (LOH) of the wild-type lrrc50 allele in 44.4% of tumor samples, correlating with tumor progression. In humans we identified heterozygous germline LRRC50 mutations in two different pedigrees with a family history of seminomas, resulting in a nonsense Arg488* change and a missense Thr590Met change, which show reduced expression of the wild-type allele in seminomas. Zebrafish in vivo complementation studies indicate the Thr590Met to be a loss-of-function mutation. Moreover, we show that a pathogenic Gln307Glu change is significantly enriched in individuals with seminoma tumors (13% of our cohort). Together, our study introduces an animal model for seminoma and suggests LRRC50 to be a novel tumor suppressor implicated in human seminoma pathogenesis

OTUB1 inhibits the ubiquitination and degradation of FOXM1 in breast cancer and epirubicin resistance

The forkhead transcription factor FOXM1 has a key role in DNA damage response, and its deregulated overexpression is associated with genotoxic drug resistance in breast cancer. However, little is known about the posttranslational mechanisms by which FOXM1 expression is regulated by genotoxic agents and how they are deregulated in resistant cells. Initial co-immunoprecipitation studies verified previous proteomic analysis finding that the OTUB1 is a novel FOXM1-interacting protein. Western blot analysis showed that both OTUB1 and FOXM1 expression reduced upon genotoxic agent treatment in MCF-7 cells, but remained relatively constant in resistant cells. FOXM1 expression reduced upon OTUB1 depletion by siRNA and increased with OTUB1 overexpression in MCF-7 cells, arguing that OTUB1 positively regulates FOXM1 expression. In agreement, co-immunoprecipitation experiments demonstrated that FOXM1 expression is associated with OTUB1 binding but inversely correlates with conjugation to the protein degradation-associated Lys-48-linked ubiquitin-chains. Overexpression of wild-type (WT) OTUB1, but not the OTUB1(C91S) mutant, disrupted the formation of Lys48-linked ubiquitin-conjugates on FOXM1. Importantly, knockdown of OTUB1 by siRNA resulted in an increase in turnover of FOXM1 in MCF-7 cells treated with the protein synthesis inhibitor cycloheximide, whereas overexpression of WT OTUB1, but not the OTUB1(C91S) mutant, significantly enhances the half-life of FOXM1. In addition, proliferative and clonogenic assays also show that OTUB1 can enhance the proliferative rate and epirubicin resistance through targeting FOXM1, as OTUB1 has little effect on FOXM1-deficient cells. The physiological relevance of the regulation of FOXM1 by OTUB1 is further underscored by the significant correlations between FOXM1 and OTUB1 expression in breast cancer patient samples. Cox-regression survival analysis indicates that OTUB1 overexpression is linked to poorer outcome in particular in patients treated with chemotherapy. Collectively, these data suggest that OTUB1 limits the ubiquitination and degradation of FOXM1 in breast cancer and has a key role in genotoxic agent resistance

Dissecting Disease-Suppressive Rhizosphere Microbiomes by Functional Amplicon Sequencing and 10x Metagenomics

Disease-suppressive soils protect plants against soilborne fungal pathogens that would otherwise cause root infections. Soil suppressiveness is, in most cases, mediated by the antagonistic activity of the microbial community associated with the plant roots. Considering the enormous taxonomic and functional diversity of the root-associated microbiome, identification of the microbial genera and mechanisms underlying this phenotype is challenging. One approach to unravel the underlying mechanisms is to identify metabolic pathways enriched in the disease-suppressive microbial community, in particular, pathways that harbor natural products with antifungal properties. An important class of these natural products includes peptides produced by nonribosomal peptide synthetases (NRPSs). Here, we applied functional amplicon sequencing of NRPS-associated adenylation domains (A domains) to a collection of eight soils that are suppressive or nonsuppressive (i.e., conducive) to Fusarium culmorum, a fungal root pathogen of wheat. To identify functional elements in the root-associated bacterial community, we developed an open-source pipeline, referred to as dom2BGC, for amplicon annotation and putative gene cluster reconstruction through analyzing A domain co-occurrence across samples. We applied this pipeline to rhizosphere communities from four disease-suppressive and four conducive soils and found significant similarities in NRPS repertoires between suppressive soils. Specifically, several siderophore biosynthetic gene clusters were consistently associated with suppressive soils, hinting at competition for iron as a potential mechanism of suppression. Finally, to validate dom2BGC and to allow more unbiased functional metagenomics, we performed 10× metagenomic sequencing of one suppressive soil, leading to the identification of multiple gene clusters potentially associated with the disease-suppressive phenotyp

Modeling Personalized Adjuvant TreaTment in EaRly stage coloN cancer (PATTERN)

Aim To develop a decision model for the population-level evaluation of strategies to improve the selection of stage II colon cancer (CC) patients who benefit from adjuvant chemotherapy. Methods A Markov cohort model with a one-month cycle length and a lifelong time horizon was developed. Five health states were included; diagnosis, 90-day mortality, death other causes, recurrence and CC death. Data from the Netherlands Cancer Registry were used to parameterize the model. Transition probabilities were estimated using parametric survival models including relevant clinical and pathological covariates. Subsequently, biomarker status was implemented using external data. Treatment effect was incorporated using pooled trial data. Model development, data sources used, parameter estimation, and internal and external validation are described in detail. To illustrate the use of the model, three example strategies were evaluated in which allocation of treatment was based on (A) 100% adherence to the Dutch guidelines, (B) observed adherence to guideline recommendations and (C) a biomarker-driven strategy. Results Overall, the model showed good internal and external validity. Age, tumor growth, tumor sidedness, evaluated lymph nodes, and biomarker status were included as covariates. For the example strategies, the model predicted 83, 87 and 77 CC deaths after 5 years in a cohort of 1000 patients for strategies A, B and C, respectively. Conclusion This model can be used to evaluate strategies for the allocation of adjuvant chemotherapy in stage II CC patients. In future studies, the model will be used to estimate population-level long-term health gain and cost-effectiveness of biomarker-based selection strategies.Financial support for this study was provided by a grant from ZonMw (Grant number: 848015007). ZonMw had no role in designing the study, interpreting the data, writing the manuscript, and publishing the report

ADAM12 is a circulating marker for stromal activation in pancreatic cancer and predicts response to chemotherapy

Pancreatic ductal adenocarcinoma (PDAC) is characterized by abundant stroma that harbors tumor-promoting properties. No good biomarkers exist to monitor the effect of stromal targeting therapies or to predict response. We set out to identify such non-invasive markers for PDAC stroma and predict response to therapy. Gene expression datasets, co-culture experiments, xenografts, and patient samples were analyzed. Serum samples were measured from a cohort of 58 resected patients, and 87 metastatic or locally advanced PDAC patients. Baseline and follow-up levels were assessed in 372 additional metastatic PDAC patients who received nab-paclitaxel with gemcitabine (n = 184) or gemcitabine monotherapy (n = 188) in the phase III MPACT trial. Increased levels of ADAM12 were found in PDAC patients compared to healthy controls (p < 0.0001, n = 157 and n = 38). High levels of ADAM12 significantly associated with poor outcome in resected PDAC (HR 2.07, p = 0.04). In the MPACT trial survival was significantly longer for patients who received nab-paclitaxel and had undetectable ADAM12 levels before treatment (OS 12.3 m vs 7.9 m p = 0.0046). Consistently undetectable or decreased ADAM12 levels during treatment significantly associated with longer survival as well (OS 14.4 m and 11.2 m, respectively vs 8.3, p = 0.0054). We conclude that ADAM12 is a blood-borne proxy for stromal activation, the levels of which have prognostic significance and correlate with treatment benefit